Variation in healthcare delivery is ubiquitous in the United States. Fundamental questions in health policy are whether greater healthcare utilization improves patient outcomes and what causes differences in utilization across regions. Reducing unwarranted variations in utilization has been viewed as an opportunity to curtail unnecessary spending, and yet the causes and consequences of variations in utilization remain incompletely understood. This study extends previous research by studying how differences in spending affect a multitude of patient self-reported outcomes related to physical, cognitive, and mental functioning and by assessing the role that health behaviors play in explaining differences in spending across regions. Study aims will be researched using data from the Health and Retirement Study (HRS), a nationally representative longitudinal survey of older Americans, linked to Medicare claims. Analytic methods include instrumental variables analysis and regression-based decomposition techniques. This study will be completed under the auspices of a larger project led by Lauren Nicholas, Ph.D., which is studying the relationships between patient factors and variation in utilization of elective surgical procedures on health and economic outcomes. Dr. Nicholas's project has demonstrated the value of HRS for studying geographic variation, determinants of Medicare spending, and interaction between socioeconomic factors and healthcare utilization. This project builds on those objectives by (1) estimating causal effects of differences in spending and utilization for patients hospitalized for acute disease episodes and those utilizing the intensive care unit, and (2) studying whether health behaviors and modifiable risk factors such as smoking, alcohol consumption, obesity, and limited physical activity explain regional variations in spending. Under the guidance of experienced mentors, this study will also equip the applicant with essential econometric skills and the facility for working with both complex survey data and claims data.